Association of Accelerometer-Determined Physical Activity and Sedentary Behavior With the Gut Microbiome in Middle-Aged Women: A Compositional Data Approach.

The beneficial effects of physical activity (PA) on gut microbiome have been reported, nevertheless the findings are inconsistent, with the main limitation of subjective methods for assessing PA. It is well accepted that using an objective assessment of PA reduces the measurement error and also allows objective assessment of sedentary behavior (SB). We aimed to study the associations between accelerometer-assessed behaviors (i.e., SB, light-intensity physical activity [LPA] and moderate-to-vigorous physical activity [MVPA]) with the gut microbiome using compositional data analysis, a novel approach that enables to study these behaviors accounting for their inter-dependency. This cross-sectional study included 289 women from the Northern Finland Birth Cohort 1966. Physical activity was measured during 14 days by wrist-worn accelerometers. Analyses based on the combined effect of MVPA and SB, and compositional data analyses in association with the gut microbiome data were performed. The microbial alpha- and beta-diversity were not significantly different between the MVPA-SB groups, and no differentially abundant microorganisms were detected. Compositional data analysis did not show any significant associations between any movement behavior (relative to the others) on microbial alpha-diversity. Butyrate-producing bacteria such as Agathobacter and Lachnospiraceae CAG56 were significantly more abundant when reallocating time from LPA or SB to MVPA (γ = 0.609 and 0.113, both p-values = 0.007). While PA and SB were not associated with microbial diversity, we found associations of these behaviors with specific gut bacteria, suggesting that PA of at least moderate intensity (i.e., MVPA) could increase the abundance of short-chain fatty acid-producing microbes.

Physical Activity, Fitness, and Cardiac Autonomic Function among Adults Born Postterm.

Recent studies have suggested that adverse outcomes of postterm birth (≥42 completed weeks of gestation), including increased cardiometabolic risk factors, impaired glucose metabolism, and obesity, may extend into adulthood. We studied interconnected determinants of cardiovascular health, including physical activity (based on accelerometry for two weeks), muscular strength (handgrip strength), cardiorespiratory fitness (4-min step test), and cardiac autonomic function (heart rate recovery, heart rate variability, and baroreflex sensitivity) among 46-year-old adults from the Northern Finland Birth Cohort (NFBC) born postterm (n = 805) and at term (n = 2,645). Adults born postterm undertook vigorous-intensity physical activity 2.0 min/day (95% CI 0.4, 3.7) less than term-born adults when adjusted for sex, age, and maternal- and pregnancy-related covariates in multiple linear regression. Postterm birth was associated with reduced cardiorespiratory fitness based on a higher peak heart rate (2.1 bpm, 95% CI 0.9, 3.4) and slower heart rate recovery 30 s after the step test (-0.7 bpm, 95% CI -1.3, -0.1). Postterm birth was associated with lower vigorous-intensity physical activity and cardiorespiratory fitness and slower heart rate recovery in middle age. Our findings reinforce previous suggestions that postterm birth should be included as a perinatal risk factor for adult cardiometabolic disease.

Associations between neighbourhood characteristics, physical activity and depressive symptoms: the Northern Finland Birth Cohort 1966 Study.

BACKGROUND: Due to rapid urbanization, there is a need to better understand the relative roles of residential environment and physical activity in depression. We aimed to investigate whether neighbourhood characteristics are related to the presence of depressive symptoms and whether the association is modified by physical activity. METHODS: This cross-sectional study used the 46-year-old follow-up data (n = 5489) from the Northern Finland Birth Cohort 1966. Data on depressive symptoms, measured by Beck Depression Inventory-II, and self-reported and accelerometer-measured physical activity were included. Neighbourhood characteristics, population density, distance to the closest grocery store, bus stops and cycle/pedestrian paths, distance to the nearest parks and forests, residential greenness and level of urbanicity were calculated using Geographic Information System methods based on participants' home coordinates. RESULTS: According to ordinal logistic regression analyses adjusted for physical activity at different intensities and individual covariates, living in a neighbourhood with higher population density and urbanicity level were associated with a higher risk of experiencing more severe depressive symptoms. Higher residential greenness was associated with a lower risk of experiencing more severe depressive symptoms after adjustment for self-reported light and moderate-to-vigorous physical activity, accelerometer-measured moderate-to-vigorous physical activity and individual covariates. Both higher self-reported and accelerometer-measured physical activity were independently associated with a lower risk of more severe depressive symptoms. CONCLUSIONS: Both residential environment and physical activity behaviour play an important role in depressive symptoms; however, further research among populations of different ages is required. Our findings can be utilized when designing interventions for the prevention of depression.

Lifestyle and Cardiac Structure and Function in Healthy Midlife Population.

The association between lifestyle and cardiac structure and function measures, such as global longitudinal strain and diastolic function in a healthy midlife general population, is not well known. A subpopulation of the Northern Finland Birth Cohort 1966 took part in follow-up, including echocardiography (n = 1,155) at the age of 46. All antihypertensive medication users (n = 164), patients with diabetes (n = 70), subjects with any cardiac diseases (n = 24), and subjects with echocardiography abnormalities (n = 21) were excluded. Moderate to vigorous physical activity (MVPA) was recorded with a wrist-worn accelerometer over 14 days and categorized into high, moderate, and low MVPA groups. Similarly, alcohol consumption was categorized as low, moderate, and high-dose users of alcohol and smoking as nonsmokers, former, and current smokers. The total number of healthy subjects included in the study was 715 (44% males). Left ventricular mass index and left atrial end-systolic volume index were significantly higher in the high MVPA group compared with the low MVPA group (adjusted main effect p = 0.002 and p <0.001, respectively). Cardiac function did not differ among the physical activity groups. High alcohol consumption was associated with impaired global longitudinal strain and diastolic function (adjusted main effect p = 0.002 and p = 0.004, respectively) but not with any cardiac structure variables. Smoking was not associated with cardiac structure or function. In healthy middle-aged adults, MVPA was independently associated with structural changes in the heart but not with cardiac function. High alcohol consumption was associated with impaired modern cardiac function measures but not with cardiac structure.

Physical activity, residential greenness, and cardiac autonomic function.

PURPOSE: This population-based study examines the associations between physical activity (PA), residential environmental greenness, and cardiac health measured by resting short-term heart rate variability (HRV). METHODS: Residential greenness of a birth cohort sample (n = 5433) at 46 years was measured with normalized difference vegetation index (NDVI) by fixing a 1 km buffer around each participant's home. Daily light PA (LPA), moderate PA (MPA), vigorous PA (VPA), and the combination of both (MVPA) were measured using a wrist-worn accelerometer for 14 days. Resting HRV was measured with a heart rate monitor, and generalized additive modeling (GAM) was used to examine the association between PA, NDVI, and resting HRV. RESULTS: In nongreen areas, men had less PA at all intensity levels compared to men in green areas. Women had more LPA and total PA and less MPA, MVPA, and VPA in green residential areas compared to nongreen areas. In green residential areas, men had more MPA, MVPA, and VPA than women, whereas women had more LPA than men. GAM showed positive linear associations between LPA, MVPA and HRV in all models. CONCLUSIONS: Higher LPA and MVPA were significantly associated with increased HRV, irrespective of residential greenness. Greenness was positively associated with PA at all intensity levels in men, whereas in women, a positive association was found for LPA and total PA. A positive relationship of PA with resting HRV and greenness with PA was found. Residential greenness for promoting PA and heart health in adults should be considered in city planning.

Association of accelerometer-measured physical activity, back static muscular endurance and abdominal obesity with radicular pain and non-specific low back pain.

Low back pain (LBP) is the leading cause of disability worldwide and often associated with lifestyle factors. However, studies further examining the role of these lifestyle factors in non-specific low back pain in comparison with radicular pain are sparse. The aim of this cross sectional study was to investigate how diverse lifestyle factors are associated with LBP. The study population of 3385 middle aged adults with and without low back pain was drawn from a large Birth 1966 Cohort. Outcome measures were steps per day, abdominal obesity, physical activity and endurance of the back muscles. Back static muscular endurance, abdominal obesity and physical activity were measured by means of the Biering-Sørensen test, waist circumference and a wrist worn accelerometer, respectively. Logistic regression analysis was applied to estimate associations of back static muscular endurance, abdominal obesity and accelerometer-measured physical activity with non-specific low back pain and radicular pain. An additional 1000 steps per day were associated with 4% lower odds of having non-specific low back pain. Participants with abdominal obesity had 46% higher odds of having radicular pain, whereas increases of 10 s in back static muscular endurance and 10 min in daily vigorous physical activity were associated with 5% and 7% lower odds of having radicular pain, respectively. In this population-based study, non-specific low back pain and radicular pain were associated with different lifestyle and physical factors at midlife. Non-specific low back pain was associated only with the average daily number of steps, whereas abdominal obesity was the strongest determinant of radicular pain, followed by vigorous physical activity and back static muscular endurance. The findings of this study contribute to better understand the role of lifestyle factors in both non-specific low back pain and radicular pain. Future longitudinal studies are required to explore causality.

Comparison and agreement between device-estimated and self-reported sleep periods in adults.

OBJECTIVES: Discriminating sleep period from accelerometer data remains a challenge despite many studies have adapted 24-h measurement protocols. We aimed to compare and examine the agreement among device-estimated and self-reported bedtime, wake-up time, and sleep periods in a sample of adults. MATERIALS AND METHODS: Participants (108 adults, 61 females) with an average age of 33.1 (SD 0.4) were asked to wear two wearable devices (Polar Active and Oura ring) simultaneously and record their bedtime and wake up time using a sleep diary. Sleep periods from Polar Active were detected using an in-lab algorithm, which is openly available. Sleep periods from Oura ring were generated by commercial Oura system. Scatter plots, Bland-Altman plots, and intraclass correlation coefficients (ICCs) were used to evaluate the agreement between the methods. RESULTS: Intraclass correlation coefficient values were above 0.81 for bedtimes and wake-up times between the three methods. In the estimation of sleep period, ICCs ranged from 0.67 (Polar Active vs. sleep diary) to 0.76 (Polar Active vs. Oura ring). Average difference between Polar Active and Oura ring was -1.8 min for bedtimes and -2.6 min for wake-up times. Corresponding values between Polar Active and sleep diary were -5.4 and -18.9 min, and between Oura ring and sleep diary -3.6 min and -16.2 min, respectively. CONCLUSION: Results showed a high agreement between Polar Active activity monitor and Oura ring for sleep period estimation. There was a moderate agreement between self-report and the two devices in estimating bedtime and wake-up time. These findings suggest that potentially wearable devices can be interchangeably used to detect sleep period, but their accuracy remains limited.Key MessagesEstimation of sleep period from different devices could be comparable.Difference between sleep periods from monitors and sleep diary are under 20 min.Device-based estimation of sleep period is encouraged in population-based studies.

Polycystic ovary syndrome is associated with weight-loss attempts and perception of overweight independent of BMI: a population-based cohort study.

OBJECTIVE: Up to 70% of women with polycystic ovary syndrome (PCOS) have pre-obesity or obesity. The aim of this study was to investigate whether women with PCOS have more weight-loss attempts than women without PCOS, regardless of BMI. Moreover, women's weight perceptions in relation to previous weight-loss attempts were evaluated. METHODS: A population-based birth cohort study included women with (n = 278) and without PCOS (control individuals, n = 1560) who were examined at ages 31 and 46 years with questionnaires and clinical examinations. RESULTS: Women with PCOS had more weight-loss attempts compared with control individuals at age 31 (47% vs. 34%, p < 0.001) and 46 years (63% vs. 47%, p < 0.001). At age 46 years, PCOS was associated with multiple weight-loss attempts in the adjusted model (odds ratio: 1.43 [95% CI: 1.00-2.03], p = 0.05). The perception of having overweight was more prevalent in those with PCOS, even among participants with normal weight, at age 31 (PCOS 47% vs. control 34%, p = 0.014) and 46 years (PCOS 60% vs. control 39%, p = 0.001). CONCLUSIONS: Women with PCOS were more likely to have experienced multiple weight-loss attempts and a perception of having overweight compared with control individuals, regardless of obesity status.

Compositional association of 24-h movement behavior with incident major adverse cardiac events and all-cause mortality.

Cardiovascular disease (CVD) causes a high disease burden. Physical activity (PA) reduces CVD morbidity and mortality. We aimed to determine the relationship between the composition of moderate-to-vigorous PA (MVPA), light PA (LPA), sedentary behavior (SB), and sleep during midlife to the incidence of major adverse cardiac events (MACE) and all-cause mortality at a 7-year follow-up. The study population consisted of Northern Finland Birth Cohort 1966 members who participated in the 46-year follow-up in 2012 and were free of MACE (N = 4147). Time spent in MVPA, LPA, and SB was determined from accelerometer data. Sleep time was self-reported. Hospital visits and deaths were obtained from national registers. Participants were followed until December 31, 2019, or first MACE occurrence (acute myocardial infarction, unstable angina pectoris, stroke, hospitalization due to heart failure, or death due to CVD), death from another cause, or censoring. Cox proportional hazards model was used to estimate hazard ratios of MACE incidence and all-cause mortality. Isotemporal time reallocations were used to demonstrate the dose-response association between time spent in behaviors and outcome. The 24-h time composition was significantly associated with incident MACE and all-cause mortality. More time in MVPA relative to other behaviors was associated with a lower risk of events. Isotemporal time reallocations indicated that the greatest risk reduction occurred when MVPA replaced sleep. Higher MVPA associates with a reduced risk of incident MACE and all-cause mortality after accounting for the 24-h movement composition and confounders. Regular engagement in MVPA should be encouraged in midlife.

Replacing sedentary time with physical activity and sleep: Associations with cardiometabolic health markers in adults.

This study aimed to examine the associations of sedentary time, and substituting sedentary time with physical activity and sleep, with cardiometabolic health markers while accounting for a full 24 h of movement and non-movement behaviors, cardiorespiratory fitness (CRF), and other potential confounders. The participants were 4585 members of the Northern Finland Birth Cohort 1966, who wore a hip-worn accelerometer at the age of 46 years for 14 consecutive days. Time spent in sedentary behaviors, light-intensity physical activity (LPA), and moderate-to-vigorous-intensity physical activity (MVPA) were determined from the accelerometer and combined with self-reported sleep duration to obtain the 24-h time use. CRF was estimated from the peak heart rate in a submaximal step test. An isotemporal substitution paradigm was used to examine how sedentary time and substituting sedentary time with an equal amount of LPA, MVPA, or sleep were associated with adiposity markers, blood lipid levels, and fasting glucose and insulin. Sedentary time was independently and adversely associated with the markers of cardiometabolic health, even after adjustment for CRF, but not in partition models including LPA, MVPA, sleep, and CRF. Substituting 60, 45, 30, and 15 min/day of sedentary time with LPA or MVPA was associated with 0.2%-13.7% favorable differences in the cardiometabolic health markers after accounting for LPA, MVPA, sleep, CRF, and other confounders. After adjustment for movement and non-movement behaviors within the 24-h cycle, reallocating additional time to both LPA and MVPA was beneficially associated with markers of cardiometabolic health in middle-aged adults regardless of their CRF level.

Joint Profiles of Sedentary Time and Physical Activity in Adults and Their Associations with Cardiometabolic Health.

PURPOSE: This study aimed to identify and characterize joint profiles of sedentary time and physical activity among adults and to investigate how these profiles are associated with markers of cardiometabolic health. METHODS: The participants included 3702 of the Northern Finland Birth Cohort 1966 at age 46 yr, who wore a hip-worn accelerometer during waking hours and provided seven consecutive days of valid data. Sedentary time, light-intensity physical activity, and moderate- to vigorous-intensity physical activity on each valid day were obtained, and a data-driven clustering approach ("KmL3D") was used to characterize distinct joint profiles of sedentary time and physical activity intensities. Participants self-reported their sleep duration and performed a submaximal step test with continuous heart rate measurement to estimate their cardiorespiratory fitness (peak heart rate). Linear regression was used to determine the association between joint profiles of sedentary time and physical activities with cardiometabolic health markers, including adiposity markers and blood lipid, glucose, and insulin levels. RESULTS: Four distinct groups were identified: "active couch potatoes" ( n = 1173), "sedentary light movers" ( n = 1199), "sedentary exercisers" ( n = 694), and "movers" ( n = 636). Although sufficiently active, active couch potatoes had the highest daily sedentary time (>10 h) and lowest light-intensity physical activity. Compared with active couch potatoes, sedentary light movers, sedentary exercisers, and movers spent less time in sedentary by performing more physical activity at light-intensity upward and had favorable differences in their cardiometabolic health markers after accounting for potential confounders (1.1%-25.0% lower values depending on the health marker and profile). CONCLUSIONS: After accounting for sleep duration and cardiorespiratory fitness, waking activity profiles characterized by performing more physical activity at light-intensity upward, resulting in less time spent in sedentary, were associated with better cardiometabolic health.

Accelerometer-measured physical activity is associated with knee breadth in middle-aged Finns - a population-based study.

BACKGROUND: Articular surface size is traditionally considered to be a relatively stable trait throughout adulthood. Increased joint size reduces bone and cartilage tissue strains. Although physical activity (PA) has a clear association with diaphyseal morphology, the association between PA and articular surface size is yet to be confirmed. This cross-sectional study aimed to clarify the role of moderate-to-vigorous PA (MVPA) in knee morphology in terms of tibiofemoral joint size. METHODS: A sample of 1508 individuals from the population-based Northern Finland Birth Cohort 1966 was used. At the age of 46, wrist-worn accelerometers were used to monitor MVPA (≥3.5 METs) during a period of two weeks, and knee radiographs were used to obtain three knee breadth measurements (femoral biepicondylar breadth, mediolateral breadth of femoral condyles, mediolateral breadth of the tibial plateau). The association between MVPA and knee breadth was analyzed using general linear models with adjustments for body mass index, smoking, education years, and accelerometer weartime. RESULTS: Of the sample, 54.8% were women. Most individuals were non-smokers (54.6%) and had 9-12 years of education (69.6%). Mean body mass index was 26.2 (standard deviation 4.3) kg/m2. MVPA was uniformly associated with all three knee breadth measurements among both women and men. For each 60 minutes/day of MVPA, the knee breadth dimensions were 1.8-2.0% (or 1.26-1.42 mm) larger among women (p < 0.001) and 1.4-1.6% (or 1.21-1.28 mm) larger among men (p < 0.001). CONCLUSIONS: Higher MVPA is associated with larger tibiofemoral joint size. Our findings indicate that MVPA could potentially increase knee dimensions through similar biomechanical mechanisms it affects diaphyseal morphology, thus offering a potential target in reducing tissue strains and preventing knee problems. Further studies are needed to confirm and investigate the association between articulation area and musculoskeletal health.

Cross-Sectional Associations of Sedentary Behavior and Sitting with Serum Lipid Biomarkers in Midlife.

INTRODUCTION: Physical inactivity, excessive total time spent in sedentary behavior (SB) and prolonged sedentary bouts have been proposed to be risk factors for chronic disease morbidity and mortality worldwide. However, which patterns and postures of SB have the most negative impacts on health outcomes is still unclear. This population-based study aimed to investigate the independent associations of the patterns of accelerometer-based overall SB and sitting with serum lipid biomarkers at different moderate- to vigorous-intensity physical activity (MVPA) levels. METHODS: Physical activity and SB were measured in a birth cohort sample ( N = 3272) at 46 yr using a triaxial hip-worn accelerometer in free-living conditions for 14 d. Raw acceleration data were classified into SB and PA using a machine learning-based model, and the bouts of overall SB and sitting were identified from the classified data. The participants also answered health-related questionnaires and participated in clinical examinations. Associations of overall SB (lying and sitting) and sitting patterns with serum lipid biomarkers were investigated using linear regression. RESULTS: The overall SB patterns were more consistently associated with serum lipid biomarkers than the sitting patterns after adjustments. Among the participants with the least and the most MVPA, high total time spent in SB and SB bouts of 15-29.99 and ≥30 min were associated with impaired lipid metabolism. Among those with moderate amount of MVPA, higher time spent in SB and SB bouts of 15-29.99 min was unfavorably associated with serum lipid biomarkers. CONCLUSIONS: The associations between SB patterns and serum lipid biomarkers were dependent on MVPA level, which should be considered when planning evidence-based interventions to decrease SB in midlife.

Machine-learning models for activity class prediction: A comparative study of feature selection and classification algorithms.

PURPOSE: Machine-learning (ML) approaches have been repeatedly coupled with raw accelerometry to classify physical activity classes, but the features required to optimize their predictive performance are still unknown. Our aim was to identify appropriate combination of feature subsets and prediction algorithms for activity class prediction from hip-based raw acceleration data. METHODS: The hip-based raw acceleration data collected from 27 participants was split into training (70 %) and validation (30 %) subsets. A total of 206 time- (TD) and frequencydomain (FD) features were extracted from 6-second non-overlapping windows of the signal. Feature selection was done using seven filter-based, two wrapper-based, and one embedded algorithm, and classification was performed with artificial neural network (ANN), support vector machine (SVM), and random forest (RF). For every combination between the feature selection method and the classifiers, the most appropriate feature subsets were found and used for model training within the training set. These models were then validated with the left-out validation set. RESULTS: The appropriate number of features for the ANN, SVM, and RF ranged from 20 to 45. Overall, the accuracy of all the three classifiers was higher when trained with feature subsets generated using filter-based methods compared with when they were trained with wrapper-based methods (range: 78.1 %-88 % vs. 66 %-83.5 %). TD features that reflect how signals vary around the mean, how they differ with one another, and how much and how often they change were more frequently selected via the feature selection methods. CONCLUSIONS: A subset of TD features from raw accelerometry could be sufficient for ML-based activity classification if properly selected from different axes.

Infant motor development and physical activity and sedentary time at midlife.

This study investigated whether the timing of infant motor development is associated with self-reported and accelerometer-measured physical activity (PA) and sedentary time (ST) in midlife. This population-based study consisted of 4098 people born in 1966 in Northern Finland (NFBC 1966). Data on nine infant motor developmental milestones included making sounds, holding up the head, grabbing objects, turning from back to tummy, sitting without support, standing with support, walking with support, standing without support, and walking without support. At the age of 46, PA at leisure time and sitting time was self-reported. PA and ST were also measured with a wrist-worn Polar Active accelerometer that was instructed to be worn on the non-dominant hand 24 h/d for 14 days. A multiple linear regression analysis was used to analyze the association between infant motor development and PA and ST in midlife. Later infant motor development was weakly associated with higher accelerometer-measured light PA, but not with moderate-to-vigorous PA. Later infant locomotor development was associated with lower accelerometer-measured ST (ß -0.07, p = 0.012) and lower self-reported sitting time at work (ß -0.06, p = 0.004) in women. In conclusion, later infant motor development was associated with higher light PA and lower sedentary time at middle age. PA is a multifactorial behavior influenced by various factors from early childhood to midlife. Further research is required before more general conclusions can be drawn.

Association Between Vertebral Dimensions and Lumbar Modic Changes.

STUDY DESIGN: Population-based birth cohort study. OBJECTIVE: The aim of this study was to evaluate the relationship between vertebral dimensions and lumbar MC. SUMMARY OF BACKGROUND DATA: Low back pain (LBP) has become the leading cause of disability worldwide. Modic changes (MC) of the lumbar spine are one potential LBP-associated etiological factor. Mechanical stress is considered to play a key role in the development of MC through damage to endplates. There is speculation that vertebral dimensions play a role in some degenerative changes in the spine. Previous studies have also shown a positive association between moderate-to-vigorous physical activity (MVPA) and both vertebral dimensions and MC. In this study, we aimed to evaluate the relationship between vertebral dimensions and MC. METHODS: The study population consisted of 1221 participants from the Northern Finland Birth Cohort 1966 who underwent lumbar magnetic resonance imaging (MRI) and physical activity measurements at the age of 46-48. The presence of Type 1 (MC1) and Type 2 (MC2) MC and the height, axial cross-sectional area (CSA), and volume of the L4 vertebra were determined from MRI scans. MVPA (≥3.5 metabolic equivalents) was measured by a wrist-worn accelerometer. We analyzed the association between lumbar MC and vertebral height, CSA, and volume using logistic regression models before and after adjustment for sex, height, weight, smoking, education level, and MVPA. RESULTS: Vertebral height was positively associated with the presence of MC2 (odds ratio [OR] 3.51; 95% confidence interval [CI] 1.43-8.65), whereas vertebral CSA was not associated with the presence of lumbar MC. Vertebral volume was positively associated with the presence of any MC (OR 1.04; 95% CI 1.00-1.07), but the association did not persist when analyzing MC1 and MC2 separately. CONCLUSION: Vertebral height was associated with the presence of MC2. Further studies are needed to clarify the role of vertebral dimensions as independent risk factors for MC.Level of Evidence: 3.

Compositional Associations of Sleep and Activities within the 24-h Cycle with Cardiometabolic Health Markers in Adults.

PURPOSE: This study aimed to examine how compositions of 24-h time use and time reallocations between movement behaviors are associated with cardiometabolic health in a population-based sample of middle-age Finnish adults. METHODS: Participants were 3443 adults 46 yr of age from the Northern Finland Birth Cohort 1966 study. Participants wore a hip-worn accelerometer for 14 d from which time spent in sedentary behavior (SB), light-intensity physical activity (LPA), and moderate- to vigorous-intensity physical activity (MVPA) were determined. These data were combined with self-reported sleep to obtain the 24-h time-use composition. Cardiometabolic outcomes included adiposity markers, blood lipid levels, and markers of glucose control and insulin sensitivity. Multivariable-adjusted regression analysis, using a compositional data analysis approach based on isometric log-ratio transformation, was used to examine associations between movement behaviors with cardiometabolic outcomes. RESULTS: More daily time in MVPA and LPA, relative to other movement behaviors, was consistently favorably associated with all cardiometabolic outcomes. For example, relative to time spent in other behaviors, 30 min·d-1 more MVPA and LPA were both associated with lower 2-h post-glucose load insulin level (-11.8% and -2.7%, respectively). Relative to other movement behaviors, more daily time in SB was adversely associated with adiposity measures, lipid levels, and markers of insulin sensitivity, and more daily time asleep was adversely associated with adiposity measures, blood lipid, fasting plasma glucose, and 2-h insulin. For example, 60 min·d-1 more SB and sleep relative to the remaining behaviors were both associated with higher 2-h insulin (3.5% and 5.7%, respectively). CONCLUSIONS: Altering daily movement behavior compositions to incorporate more MVPA at the expense of any other movement behavior, or more LPA at the expense of SB or sleep, could help to improve cardiometabolic health in midadulthood.

Satellite Imaging-Based Residential Greenness and Accelerometry Measured Physical Activity at Midlife-Population-Based Northern Finland Birth Cohort 1966 Study.

BACKGROUND: Recently, the importance of light physical activity (LPA) for health has been emphasized, and residential greenness has been positively linked to the level of LPA and a variety of positive health outcomes. However, people spend less time in green environments because of urbanization and modern sedentary leisure activities. AIMS: In this population-based study, we investigated the association between objectively measured residential greenness and accelerometry measured physical activity (PA), with a special interest in LPA and gender differences. METHODS: The study was based on the Northern Finland Birth Cohort 1966 (5433 members). Participants filled in a postal questionnaire and underwent clinical examinations and wore a continuous measurement of PA with wrist-worn Polar Active Activity Monitor accelerometers for two weeks. The volume of PA (metabolic equivalent of task or MET) was used to describe the participant's total daily activity (light: 2-3.49 MET; moderate: 3.5-4.99 MET; vigorous: 5-7.99 MET; very vigorous: ≥8 MET). A geographic information system (GIS) was used to assess the features of each individual's residential environment. The normalized difference vegetation index (NDVI) was used for the objective quantification of residential greenness. Multiple linear regression and a generalized additive model (GAM) were used to analyze the association between residential greenness and the amount of PA at different intensity levels. RESULTS: Residential greenness (NDVI) was independently associated with LPA (unadjusted ß = 174; CI = 140, 209) and moderate physical activity (MPA) (unadjusted ß = 75; CI = 48, 101). In the adjusted model, residential greenness was positively and significantly associated with LPA (adjusted ß = 70; CI = 26, 114). In men, residential greenness was positively and significantly associated with LPA (unadjusted ß = 224; CI = 173, 275), MPA (unadjusted ß = 75; CI = 48, 101), and moderate to vigorous physical activity (MVPA) (unadjusted ß = 89; CI = 25, 152). In women, residential greenness was positively related to LPA (unadjusted ß = 142; CI = 96, 188) and inversely associated with MPA (unadjusted ß = -22; CI = -36, -8), vigorous/very vigorous physical activity (VPA/VVPA) (unadjusted ß = -49; CI = -84, -14), and MVPA (unadjusted ß = -71; CI = -113, -29). In the final adjusted models, residential greenness was significantly associated only with the amount of LPA in men (adjusted ß = 140; CI = 75, 204). CONCLUSIONS: Residential greenness was positively associated with LPA in both genders, but the association remained significant after adjustments only in men. Residential greenness may provide a supportive environment for promoting LPA.

Association between device-measured physical activity and lumbar Modic changes.

BACKGROUND: Modic changes (MC) in the lumbar spine are considered one potential etiological factor behind low back pain (LBP). Multiple risk factors for MC have been suggested, including male gender, smoking and factors affecting hyperloading and mechanical stress such as high body mass index (BMI), strenuous physical work and high occupational and leisure-time physical activity (PA). So far, the effect of PA on the occurrence of MC has remained under debate due to contradictory findings. The purpose of this study was to investigate the possible association between device-measured moderate-to-vigorous PA (MVPA) (≥ 3.5 METs) and lumbar MC. METHODS: The study had 1374 participants from the Northern Finland Birth Cohort 1966. At the age of 46-48, PA was measured by a wrist-worn accelerometer, and lumbar magnetic resonance imaging (MRI) was carried out to determine MC. We analyzed the association between Type 1 (MC1) and Type 2 (MC2) MC and daily amount of MVPA (min/day) using sex-stratified logistic regression models before and after adjustment for BMI, socioeconomic status, smoking, and accelerometer wear time. RESULTS: Among men, increased amount of MVPA was positively associated with any MC (adjusted OR corresponding to every 60 min/day of MVPA 1.41; 95% confidence interval (CI) 1.01 to 1.95) and MC2 (OR 1.54; 95% CI 1.14 to 2.08), but not with MC1 (OR 1.06; 95% CI 0.80 to 1.39). Among women, we only found a positive association between MVPA and MC1 before adjustments (unadjusted OR 1.42; 95% CI 1.06 to 1.92). CONCLUSION: Among men, increased amount of MVPA was associated with increased odds of any MC and particularly MC2. Among women, MVPA was not independently associated with MC.

Correlates of physical activity behavior in adults: a data mining approach.

PURPOSE: A data mining approach was applied to establish a multilevel hierarchy predicting physical activity (PA) behavior, and to methodologically identify the correlates of PA behavior. METHODS: Cross-sectional data from the population-based Northern Finland Birth Cohort 1966 study, collected in the most recent follow-up at age 46, were used to create a hierarchy using the chi-square automatic interaction detection (CHAID) decision tree technique for predicting PA behavior. PA behavior is defined as active or inactive based on machine-learned activity profiles, which were previously created through a multidimensional (clustering) approach on continuous accelerometer-measured activity intensities in one week. The input variables (predictors) used for decision tree fitting consisted of individual, demographical, psychological, behavioral, environmental, and physical factors. Using generalized linear mixed models, we also analyzed how factors emerging from the model were associated with three PA metrics, including daily time (minutes per day) in sedentary (SED), light PA (LPA), and moderate-to-vigorous PA (MVPA), to assure the relative importance of methodologically identified factors. RESULTS: Of the 4582 participants with valid accelerometer data at the latest follow-up, 2701 and 1881 had active and inactive profiles, respectively. We used a total of 168 factors as input variables to classify these two PA behaviors. Out of these 168 factors, the decision tree selected 36 factors of different domains from which 54 subgroups of participants were formed. The emerging factors from the model explained minutes per day in SED, LPA, and/or MVPA, including body fat percentage (SED: B = 26.5, LPA: B = - 16.1, and MVPA: B = - 11.7), normalized heart rate recovery 60 s after exercise (SED: B = -16.1, LPA: B = 9.9, and MVPA: B = 9.6), average weekday total sitting time (SED: B = 34.1, LPA: B = -25.3, and MVPA: B = -5.8), and extravagance score (SED: B = 6.3 and LPA: B = - 3.7). CONCLUSIONS: Using data mining, we established a data-driven model composed of 36 different factors of relative importance from empirical data. This model may be used to identify subgroups for multilevel intervention allocation and design. Additionally, this study methodologically discovered an extensive set of factors that can be a basis for additional hypothesis testing in PA correlates research.